R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(93.2
+ ,96
+ ,95.2
+ ,77.1
+ ,70.9
+ ,64.8
+ ,70.1
+ ,77.3
+ ,79.5
+ ,100.6
+ ,100.7
+ ,107.1
+ ,95.9
+ ,82.8
+ ,83.3
+ ,80
+ ,80.4
+ ,67.5
+ ,75.7
+ ,71.1
+ ,89.3
+ ,101.1
+ ,105.2
+ ,114.1
+ ,96.3
+ ,84.4
+ ,91.2
+ ,81.9
+ ,80.5
+ ,70.4
+ ,74.8
+ ,75.9
+ ,86.3
+ ,98.7
+ ,100.9
+ ,113.8
+ ,89.8
+ ,84.4
+ ,87.2
+ ,85.6
+ ,72
+ ,69.2
+ ,77.5
+ ,78.1
+ ,94.3
+ ,97.7
+ ,100.2
+ ,116.4
+ ,97.1
+ ,93
+ ,96
+ ,80.5
+ ,76.1
+ ,69.9
+ ,73.6
+ ,92.6
+ ,94.2
+ ,93.5
+ ,108.5
+ ,109.4
+ ,105.1
+ ,92.5
+ ,97.1
+ ,81.4
+ ,79.1
+ ,72.1
+ ,78.7
+ ,87.1
+ ,91.4
+ ,109.9
+ ,116.3
+ ,113
+ ,100
+ ,84.8
+ ,94.3
+ ,87.1
+ ,90.3
+ ,72.4
+ ,84.9
+ ,92.7
+ ,92.2
+ ,114.9
+ ,112.5
+ ,118.3
+ ,106
+ ,91.2
+ ,96.6
+ ,96.3
+ ,88.2
+ ,70.2
+ ,86.5
+ ,88.2
+ ,102.8
+ ,119.1
+ ,119.2
+ ,125.1
+ ,106.1
+ ,102.1
+ ,105.2
+ ,101
+ ,84.3
+ ,87.5
+ ,92.7
+ ,94.4
+ ,113
+ ,113.9
+ ,122.9
+ ,132.7
+ ,106.9
+ ,96.6
+ ,127.3
+ ,98.2
+ ,100.2
+ ,89.4
+ ,95.3
+ ,104.2
+ ,106.4
+ ,116.2
+ ,135.9
+ ,134
+ ,104.6
+ ,107.1
+ ,123.5
+ ,98.8
+ ,98.6
+ ,90.6
+ ,89.1
+ ,105.2
+ ,114
+ ,122.1
+ ,138
+ ,142.2
+ ,116.4
+ ,112.6
+ ,123.8
+ ,103.6
+ ,113.9
+ ,98.6
+ ,95
+ ,116
+ ,113.9
+ ,127.5
+ ,131.4
+ ,145.9
+ ,131.5
+ ,131
+ ,130.5
+ ,118.9
+ ,114.3
+ ,85.7
+ ,104.6
+ ,105.1
+ ,117.3
+ ,142.5
+ ,140
+ ,159.8
+ ,131.2
+ ,125.4
+ ,126.5
+ ,119.4
+ ,113.5
+ ,98.7
+ ,114.5
+ ,113.8
+ ,133.1
+ ,143.4
+ ,137.3
+ ,165.2
+ ,126.9
+ ,124
+ ,135.7
+ ,130
+ ,109.4
+ ,117.8
+ ,120.3
+ ,121
+ ,132.3
+ ,142.9
+ ,147.4
+ ,175.9
+ ,132.6
+ ,123.7
+ ,153.3
+ ,134
+ ,119.6
+ ,116.2
+ ,118.6
+ ,130.7
+ ,129.3
+ ,144.4
+ ,163.2
+ ,179.4
+ ,128.1
+ ,138.4
+ ,152.7
+ ,120
+ ,140.5
+ ,116.2
+ ,121.4
+ ,127.8
+ ,143.6
+ ,157.6
+ ,166.2
+ ,182.3
+ ,153.1
+ ,147.6
+ ,157.7
+ ,137.2
+ ,151.5
+ ,98.7
+ ,145.8
+ ,151.7
+ ,129.4
+ ,174.1
+ ,197
+ ,193.9
+ ,164.1
+ ,142.8
+ ,157.9
+ ,159.2
+ ,162.2
+ ,123.1
+ ,130
+ ,150.1
+ ,169.4
+ ,179.7
+ ,182.1
+ ,194.3
+ ,161.4
+ ,169.4
+ ,168.8
+ ,158.1
+ ,158.5
+ ,135.3
+ ,149.3
+ ,143.4
+ ,142.2
+ ,188.4
+ ,166.2
+ ,199.2
+ ,182.7
+ ,145.2
+ ,182.1
+ ,158.7
+ ,141.6
+ ,132.6
+ ,139.6
+ ,147
+ ,166.6
+ ,157
+ ,180.4
+ ,210.2
+ ,159.8
+ ,157.8
+ ,168.2
+ ,158.4
+ ,152
+ ,142.2
+ ,137.2
+ ,152.6
+ ,166.8
+ ,165.6
+ ,198.6
+ ,201.5
+ ,170.7
+ ,164.4
+ ,179.7
+ ,157
+ ,168
+ ,139.3
+ ,138.6
+ ,153.4
+ ,138.9
+ ,172.1
+ ,198.4
+ ,217.8
+ ,173.7
+ ,153.8
+ ,175.6
+ ,147.1
+ ,160.3
+ ,135.2
+ ,148.8
+ ,151
+ ,148.2
+ ,182.2
+ ,189.2
+ ,183.1
+ ,170
+ ,158.4
+ ,176.1
+ ,156.2
+ ,153.2
+ ,117.9
+ ,149.8
+ ,156.6
+ ,166.7
+ ,156.8
+ ,158.6
+ ,210.8
+ ,203.6
+ ,175.2
+ ,168.7
+ ,155.9
+ ,147.3
+ ,137
+ ,141.1
+ ,167.4
+ ,160.2
+ ,191.9
+ ,174.4
+ ,208.2
+ ,159.4
+ ,161.1
+ ,172.1
+ ,158.4
+ ,114.6
+ ,159.6
+ ,159.7
+ ,159.4
+ ,160.7
+ ,165.5
+ ,205
+ ,205.2
+ ,141.6
+ ,148.1
+ ,184.9
+ ,132.5
+ ,137.3
+ ,135.5
+ ,121.7
+ ,166.1
+ ,146.8
+ ,162.8
+ ,186.8
+ ,185.5
+ ,151.5
+ ,158.1
+ ,143
+ ,151.2
+ ,147.6
+ ,130.7
+ ,137.5
+ ,146.1
+ ,133.6
+ ,167.9
+ ,181.9
+ ,202
+ ,166.5
+ ,151.3
+ ,146.2
+ ,148.3
+ ,144.7
+ ,123.6
+ ,151.6
+ ,133.9
+ ,137.4
+ ,181.6
+ ,182
+ ,190
+ ,161.2
+ ,155.5
+ ,141.9
+ ,164.6
+ ,136.2
+ ,126.8
+ ,152.5
+ ,126.6
+ ,150.1
+ ,186.3
+ ,147.5
+ ,200.4
+ ,177.2
+ ,127.4
+ ,177.1
+ ,154.4
+ ,135.2
+ ,126.4
+ ,147.3
+ ,140.6
+ ,152.3
+ ,151.2
+ ,172.2
+ ,215.3
+ ,154.1
+ ,159.3
+ ,160.4
+ ,151.9
+ ,148.4
+ ,139.6
+ ,148.2
+ ,153.5
+ ,145.1
+ ,183.7
+ ,210.5
+ ,203.3
+ ,153.3
+ ,144.3
+ ,169.6
+ ,143.7
+ ,160.1
+ ,135.6
+ ,141.8
+ ,159.9
+ ,145.7
+ ,183.5
+ ,198.2
+ ,186.8
+ ,172
+ ,150.6
+ ,163.3
+ ,153.7
+ ,152.9
+ ,135.5
+ ,148.5
+ ,148.4
+ ,133.6
+ ,194.1
+ ,208.6
+ ,197.3
+ ,164.4
+ ,148.1
+ ,152
+ ,144.1
+ ,155
+ ,124.5
+ ,153
+ ,146
+ ,138
+ ,190
+ ,192
+ ,192
+ ,147
+ ,133
+ ,163
+ ,150
+ ,129
+ ,131
+ ,145
+ ,137
+ ,138
+ ,168
+ ,176
+ ,188
+ ,139
+ ,143
+ ,150
+ ,154
+ ,137
+ ,129
+ ,128
+ ,140
+ ,143
+ ,151
+ ,177
+ ,184
+ ,151
+ ,134
+ ,164
+ ,126
+ ,131
+ ,125
+ ,127
+ ,143
+ ,143
+ ,160
+ ,190
+ ,182
+ ,138
+ ,136
+ ,152
+ ,127
+ ,151
+ ,130
+ ,119
+ ,153)
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/rcomp/tmp/1qco11272898851.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/2qco11272898851.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1] 1.0000000 0.8287035 0.7357571 0.6817643 0.5951505 0.5604500 0.5071206
 [8] 0.5318040 0.5995335 0.6602528 0.7068292 0.8196599 0.8963575 0.7847054
[15] 0.7185151 0.6302913 0.5536634 0.5305491 0.4598402 0.5030353 0.5612642
[22] 0.6000449 0.6672662 0.7708268 0.8323549 0.7470216 0.6750322 0.5785639
[29] 0.5204331 0.4828007 0.4002275 0.4648531 0.5185168 0.5426830 0.6338271
[36] 0.7120026 0.7705587 0.7104989 0.6028971 0.5212515 0.4825605 0.4197625
[43] 0.3494458 0.4269037 0.4462374 0.4921750 0.5889398 0.6346109 0.7134887
> (mypacf <- c(rpacf$acf))
 [1]  0.828703501  0.156448476  0.123635243 -0.073867924  0.108689719
 [6] -0.035615760  0.260935255  0.263915262  0.256605958  0.126321720
[11]  0.486938234  0.462010196 -0.230884290 -0.098141621 -0.198970847
[16] -0.170595289 -0.008927693 -0.070291672  0.081444982 -0.048800456
[21] -0.034376141 -0.066095103  0.088324751  0.236768970 -0.037680704
[26] -0.020613218 -0.084181880 -0.061949424 -0.041637149 -0.144407390
[31]  0.101743387  0.081609385 -0.068078183  0.063292114 -0.039782252
[36]  0.067233367 -0.010097229 -0.167305061 -0.023314502  0.057747150
[41]  0.006536138 -0.092497298  0.114316838 -0.095344527 -0.068016453
[46]  0.096534216 -0.045968305  0.041813083
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 2:(par1+1)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i-1,header=TRUE)
+ a<-table.element(a,round(myacf[i],6))
+ mytstat <- myacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/3mm491272898851.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:par1) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,round(mypacf[i],6))
+ mytstat <- mypacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4xd3u1272898851.tab") 
> 
> try(system("convert tmp/1qco11272898851.ps tmp/1qco11272898851.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qco11272898851.ps tmp/2qco11272898851.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.740   0.530   0.998